How it works

Three ways to run a test

Start with one prompt, run a batch of categories on a schedule, or hand the conversation to an attacker model. Every path is graded by the same engine and lands in the same evidence trail.

Start here

Threat model your use case LLM application

Describe what your application does, who uses it, and the data or tools it can access. Necio suggests the threat models that fit your use case, such as hallucination, prompt injection or reasoning, and writes five tailored test prompts for each one, mapped to OWASP risks.

Watch the walkthrough on YouTube →

1

One prompt, on demand

Write your own ad-hoc prompt, or describe your system and objective and let the Agentic Prompt Orchestrator generate one with OWASP risk mapping, severity, grading criteria, and suggested fixes. Send it once against any target and read the graded result.

Optional verified Base64, UTF-8 decimal, or emoji-steganography encoding, plus file attachments for attacks delivered through documents and images.

Target blocks automated browsers? Run it as an Assisted Scan: you send the prompt from your own browser, and the Necio Assist Chrome extension can fill it in and bring the reply back for grading.

2

Category batches, once or on a schedule

Run a batch of prompts grouped by category (built-in templates or suites generated for your own use case) as a one-time scan or on a recurring schedule.

Repeat runs are what make drift visible. Necio compares each response against the previous run and the approved baseline, then reports confirmed changes in grade, risk, and behavior.

3

Maestro adversarial conversation

LLM versus LLM, crescendo style. You set the scenario, the objective, and the turn limit; an attacker model opens and adapts every following prompt to what your target just said, escalating instead of replaying a fixed script.

Scenarios cover model distillation resistance, prompt injection, secret exposure, tool misuse, goal hijacking, memory poisoning, privilege abuse, social engineering, high-risk advice, hallucination, bias, and safety.

What you get back

Necio threat models, continuously monitors, and evaluates your Use Case LLM Applications through prompt-based vulnerability testing, behavioral integrity analysis, and compliance reporting. It identifies security gaps aligned with the OWASP Top 10 for AI and LLM-integrated systems, tracks behavioral drift over time, and integrates seamlessly with your SIEM, delivering continuous assurance across every model in production.

Necio dashboard: severe findings, behavioral drift status, hallucinations and available credit, above recent scans, a report card of unique findings by severity, and the weighted pass score
Necio analytics: severe findings, confirmed drifts, passed tests, prompts graded and hallucinations, above failed prompts by category, the severity report card, and the observed pass rate with risk posture

Mixture-of-Agents grading

At its core is our proprietary Mixture-of-Agents (MoA) grading engine: multiple specialized AI agents independently grade every result for truth, vulnerabilities, behavioral drift, and hallucinations, then consolidate their verdicts into a single high-confidence finding.

Two-Level Hallucination Verification

Necio’s hallucination workflow first uses natural language inference to calculate intrinsic and extrinsic claim rates. Deep Verification can then evaluate three independent judgment samples with per-claim majority voting, citation checks, and an agreement score, routing uncertain results to human review. These quantitative signals add transparent evidence without changing vulnerability grades or drift severity.

“There is no finite set of guardrails that is universally robust against adversarial prompts.”NIST, June 2026 (IEEE Security & Privacy)